数字农科院2.0

A novel HCR-CRISPR/Cas12a immunosensor for the sensitive detection of pesticide residues in animal-derived foods

文献类型： 外文期刊

作者： Yuanshang Wang;Pengfei Du;Xiaohong Wang;Jia Wang;Youyou Lu;Feng He;Haijie Wang;Weiting Wang;Yaobo Liu;Shoujing Wang;Jianfang Cao;Yanli Ma;A. M. Abd El-Aty

作者机构：

关键词： Animal-derived food;CRISPR/Cas12a;Gold nanoparticles;Hybridization chain reaction;Immunosensor;Pesticide residue

期刊名称： Food Bioscience

ISSN： 2212-4292

年卷期： 2024 年 62 卷

页码：

收录情况： SCIE（2024版） ; ; 农林核心（2020版）

摘要： Pesticides are widely used in the cultivation and breeding of agricultural products. However, pesticide residue monitoring has focused mainly on fruits and vegetables and has not focused on animal-derived foods. Therefore, a novel approach for determining pesticide residues in animal-derived food products via an immunosensor based on a chain hybridization reaction (HCR) with CRISPR/Cas12a is presented. Triazophos pesticide was used as a research object. This method establishes a competitive immunoreaction system in which OVA-hapten is encapsulated on the surface of the enzyme label plate, competing with pesticide molecules bound to antibodies on the surface of the nanogold composite probe. Integrating the immunoreaction with two signal amplification mechanisms, HCR and CRISPR/Cas12a, ensures heightened method sensitivity while maintaining enhanced convenience and speed. The method's detection range spans from 0.01 to 50 ng/mL, with a remarkably low detection limit of 0.013 ng/mL. Moreover, in practical sample applications, the assay exhibited a robust correlation with GC‒MS. This approach uniquely offers real-time, cost-effective, and onsite data, providing a more comprehensive and timely foundation for establishing standards on pesticide residues in animal-derived foods, bolstering food safety surveillance, and upholding public health. Moreover, the proposed HCR-CRISPR/Cas12a immunosensor effectively improved the sensitivity and accuracy of pesticides detection, offering a promising and versatile platform for food safety detection.

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